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Restricted solid on solid surface growth models can be mapped onto binary lattice gases. We show that efficient simulation algorithms can be realized on GPUs either by CUDA or by OpenCL programming. We consider a deposition/evaporation…

Computational Physics · Physics 2015-03-17 Henrik Schulz , Géza Ódor , Gergely Ódor , Máté Ferenc Nagy

We consider Monte Carlo simulations of classical spin models of statistical mechanics using the massively parallel architecture provided by graphics processing units (GPUs). We discuss simulations of models with discrete and continuous…

Computational Physics · Physics 2012-07-20 Martin Weigel , Taras Yavors'kii

We present a case-study on the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods. Graphics cards, containing multiple Graphics Processing Units (GPUs), are self-contained parallel…

Computation · Statistics 2015-05-05 Anthony Lee , Christopher Yau , Michael B. Giles , Arnaud Doucet , Christopher C. Holmes

We discuss the advantages of parallelization by multithreading on graphics processing units (GPUs) for parallel tempering Monte Carlo computer simulations of an exemplified bead-spring model for homopolymers. Since the sampling of a large…

Computational Physics · Physics 2015-05-28 Jonathan Groß , Wolfhard Janke , Michael Bachmann

We show that efficient simulations of the Kardar-Parisi-Zhang interface growth in 2 + 1 dimensions and of the 3-dimensional Kinetic Monte Carlo of thermally activated diffusion can be realized both on GPUs and modern CPUs. In this article…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-01-21 Jeffrey Kelling , Géza Ódor , Máté Ferenc Nagy , Henrik Schulz , Karl-Heinz Heinig

In this work we present an efficient implementation of Canonical Monte Carlo simulation for Coulomb many body systems on graphics processing units (GPU). Our method takes advantage of the GPU Single Instruction, Multiple Data (SIMD)…

Computational Physics · Physics 2017-03-13 Yihao Liang , Xiangjun Xing , Yaohang Li

Lattice spin models are useful for studying critical phenomena and allow the extraction of equilibrium and dynamical properties. Simulations of such systems are usually based on Monte Carlo (MC) techniques, and the main difficulty is often…

Computational Physics · Physics 2012-09-13 Tal Levy , Guy Cohen , Eran Rabani

Simulations of systems with quenched disorder are extremely demanding, suffering from the combined effect of slow relaxation and the need of performing the disorder average. As a consequence, new algorithms, improved implementations, and…

Computational Physics · Physics 2020-05-20 Ravinder Kumar , Jonathan Gross , Wolfhard Janke , Martin Weigel

A high-performance implementation of a multiphase lattice Boltzmann method based on the conservative Allen-Cahn model supporting high-density ratios and high Reynolds numbers is presented. Metaprogramming techniques are used to generate…

Fluid Dynamics · Physics 2020-12-14 Markus Holzer , Martin Bauer , Ulrich Rüde

In this paper we analyze, evaluate, and improve the performance of training generalized linear models on modern CPUs. We start with a state-of-the-art asynchronous parallel training algorithm, identify system-level performance bottlenecks,…

Machine Learning · Computer Science 2018-12-20 Nikolas Ioannou , Celestine Dünner , Kornilios Kourtis , Thomas Parnell

Simulations of physical phenomena are essential to the expedient design of precision components in aerospace and other high-tech industries. These phenomena are often described by mathematical models involving partial differential equations…

Computational Physics · Physics 2017-01-05 Daniel Magee , Kyle E Niemeyer

Over the past five years, graphics processing units (GPUs) have had a transformational effect on numerical lattice quantum chromodynamics (LQCD) calculations in nuclear and particle physics. While GPUs have been applied with great success…

High Energy Physics - Lattice · Physics 2016-11-15 R. Babich , M. A. Clark , B. Joó , G. Shi , R. C. Brower , S. Gottlieb

To effectively control large-scale distributed systems online, model predictive control (MPC) has to swiftly solve the underlying high-dimensional optimization. There are multiple techniques applied to accelerate the solving process in the…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-03-30 Carmen Amo Alonso , Shih-Hao Tseng

The standard kinetic Monte Carlo algorithm is an extremely efficient method to carry out serial simulations of dynamical processes such as thin-film growth. However, in some cases it is necessary to study systems over extended time and…

Materials Science · Physics 2007-05-23 Yunsic Shim , Jacques G. Amar

Matrix multiplication is a foundational operation in scientific computing and machine learning, yet its computational complexity makes it a significant bottleneck for large-scale applications. The shift to parallel architectures, primarily…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-07-30 Mufakir Qamar Ansari , Mudabir Qamar Ansari

We discuss the efficiency of parallelization on graphical processing units (GPUs) for the simulation of the one dimensional Potts model with long range interactions via parallel tempering. We investigate the behaviour of some thermodynamic…

Statistical Mechanics · Physics 2015-06-17 A. Boer

Micro-macro models provide a powerful tool to study the relationship between microscale mechanisms and emergent macroscopic behavior. However, the detailed microscopic modeling may require tracking and evolving a high-dimensional…

Computational Physics · Physics 2019-08-13 Steven Cook , Tamar Shinar

The octahedron model introduced recently has been implemented onto graphics cards, which permits extremely large scale simulations via binary lattice gases and bit coded algorithms. We confirm scaling behaviour belonging to the 2d…

Statistical Mechanics · Physics 2015-03-19 Jeffrey Kelling , Géza Ódor

This article introduces a highly parallel algorithm for molecular dynamics simulations with short-range forces on single node multi- and many-core systems. The algorithm is designed to achieve high parallel speedups for strongly…

Computational Physics · Physics 2013-11-20 R. Meyer

The past decade has witnessed a dramatic acceleration of lattice quantum chromodynamics calculations in nuclear and particle physics. This has been due to both significant progress in accelerating the iterative linear solvers using…

High Energy Physics - Lattice · Physics 2016-12-26 M. A. Clark , Bálint Joó , Alexei Strelchenko , Michael Cheng , Arjun Gambhir , Richard Brower
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